Computer Science ›› 2020, Vol. 47 ›› Issue (3): 287-291.doi: 10.11896/jsjkx.190200332
• Information Security • Previous Articles Next Articles
HU Jian-wei,XU Ming-yang,CUI Yan-peng
CLC Number:
[1]YONG B,LIU X,LIU Y,et al.Web Behavior Detection Based on Deep Neural Network[C]∥2018 IEEE SmartWorld,Ubiquitous Intelligence & Computing.IEEE,2018:1911-1916. [2]PENG T,QIU W D,ZHENG H,et al.SQL Injection Behavior Mining Based Deep Learning[C]∥Proceedings of 14th International Conference.Nanjing,China,2018. [3]ECKERSLEY P.How unique is your web browser? [C]∥Proceedings of the 10th International Conferenceon Privacy Enhan- cing Technologies.Berlin:Springer,Heidelberg,2010:1-18. [4]NAKIBLY G,SHELEF G,YUDILEVICH S.Hardware fingerprinting using HTML5[J].arXiv:1503.01408,2015. [5]CAO Y Z,LI S,WIJMANS E.Browser fingerprinting via OS and hardware level features[C]∥Proceedings of Network & Distributed System Security Symposium (NDSS).2017. [6]GOOGLE.HTTPS encryption on the web [EB/OL].https://trans parencyreport.google.com/https/overview. [7]W3TECHS.Usage of Default protocol https for websites[EB/OL].https://w3techs.com/technologies/details/ce-httpsdefault/all/all. [8]IVAN.Examples of the information col- lected from SSL handshakes [EB/OL].http://blog.ivanristic.com/2009/07/examples-of-the-information-collected-from-ssl-handshakes.html. [9]MAREK.SSL fingerprinting for p0f [EB/OL].https://idea. popc ount.org/2012-06-17-ssl-fingerprinting-for-p0f. [10]LEE B.Stealthier Attacks & Smarter Defending with TLS Fingerprint [EB/OL].http://blog.squarelemon.com/tls-fingerprinting. [11]HUSÁK M,CERMÁK M,JIRSÍK T,et al.HTTPS traffic ana- lysis and client identification using passive SSL/TLS fingerprin-ting[J].EURASIP Journal on Information Security,2016,2016(1):6. [12]ALTHOUSE J.Open Sourcing JA3 [EB/OL].https://engi- neering.salesforce.com/open-sourcing-ja3-92c9e53c3c41. [13]DIERKS T,RESCORLA E.The transport layer security (TLS) protocol version 1.2[OL].https://datatracker.ietf.org/doc/rfc5246/. [14]GOOGLE.Applying GREASE to TLS Extensibility,IETF Draft[OL].https://mailarchive.ietf.org/arch/msg/ietf-announce/15r5EP6SEBb8zA-T5UoeMo5OFyg/. [15]ZHANG M,XU B Y,BAI S,et al.A Deep Learning Method to Detect Web Attacks Using a Specially Designed CNN[C]∥International Conference on Neural Information Processing.Springer,Cham,2017:828-836. [16]SAXE J,BERLIN K.eXpose:A character-level convolutional neural network with embeddings for detecting malicious URLs,file paths and registry keys[J].arXiv:1702.08568,2017. [17]LE H,PHAM Q,SAHOO D,et al.URLNet:Learning a URL Representation with Deep Learning for Malicious URL Detection[J].arXiv:1802.03162,2018. [18]KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Imagenet classification with deep convolutional neural networks [C]∥Advances in Neural Information Processing Systems.2012:1097-1105. |
[1] | ZHOU Le-yuan, ZHANG Jian-hua, YUAN Tian-tian, CHEN Sheng-yong. Sequence-to-Sequence Chinese Continuous Sign Language Recognition and Translation with Multi- layer Attention Mechanism Fusion [J]. Computer Science, 2022, 49(9): 155-161. |
[2] | CHEN Yong-quan, JIANG Ying. Analysis Method of APP User Behavior Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(8): 78-85. |
[3] | ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119. |
[4] | DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang. Super-resolution Reconstruction of MRI Based on DNGAN [J]. Computer Science, 2022, 49(7): 113-119. |
[5] | LIU Yue-hong, NIU Shao-hua, SHEN Xian-hao. Virtual Reality Video Intraframe Prediction Coding Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(7): 127-131. |
[6] | XU Ming-ke, ZHANG Fan. Head Fusion:A Method to Improve Accuracy and Robustness of Speech Emotion Recognition [J]. Computer Science, 2022, 49(7): 132-141. |
[7] | WU Zi-bin, YAN Qiao. Projected Gradient Descent Algorithm with Momentum [J]. Computer Science, 2022, 49(6A): 178-183. |
[8] | YANG Yue, FENG Tao, LIANG Hong, YANG Yang. Image Arbitrary Style Transfer via Criss-cross Attention [J]. Computer Science, 2022, 49(6A): 345-352. |
[9] | YANG Jian-nan, ZHANG Fan. Classification Method for Small Crops Combining Dual Attention Mechanisms and Hierarchical Network Structure [J]. Computer Science, 2022, 49(6A): 353-357. |
[10] | ZHANG Jia-hao, LIU Feng, QI Jia-yin. Lightweight Micro-expression Recognition Architecture Based on Bottleneck Transformer [J]. Computer Science, 2022, 49(6A): 370-377. |
[11] | WANG Jian-ming, CHEN Xiang-yu, YANG Zi-zhong, SHI Chen-yang, ZHANG Yu-hang, QIAN Zheng-kun. Influence of Different Data Augmentation Methods on Model Recognition Accuracy [J]. Computer Science, 2022, 49(6A): 418-423. |
[12] | SUN Jie-qi, LI Ya-feng, ZHANG Wen-bo, LIU Peng-hui. Dual-field Feature Fusion Deep Convolutional Neural Network Based on Discrete Wavelet Transformation [J]. Computer Science, 2022, 49(6A): 434-440. |
[13] | ZHAO Zheng-peng, LI Jun-gang, PU Yuan-yuan. Low-light Image Enhancement Based on Retinex Theory by Convolutional Neural Network [J]. Computer Science, 2022, 49(6): 199-209. |
[14] | LIU Lin-yun, CHEN Kai-yan, LI Xiong-wei, ZHANG Yang, XIE Fang-fang. Overview of Side Channel Analysis Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(5): 296-302. |
[15] | ZHANG Wen-xuan, WU Qin. Fine-grained Image Classification Based on Multi-branch Attention-augmentation [J]. Computer Science, 2022, 49(5): 105-112. |
|